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Record W4414751061 · doi:10.1123/jcsp.2024-0064

Suicidality Among Canadian University Student-Athletes

2025· article· en· W4414751061 on OpenAlexaffabout
Philip Sullivan, Quinten A. Carfagnini, Burgandy Thiessen

Bibliographic record

VenueJournal of Clinical Sport Psychology · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsBrock University
Fundersnot available
KeywordsGeneralizability theorySuicidal ideationAthletesCohortSuicide preventionSuicide ideationMental healthOccupational safety and health

Abstract

fetched live from OpenAlex

Suicide is the second most common cause of death among student-athletes. It has been consistently found that the prevalence of suicidal ideation among student-athletes is similar to, or lower than, nonathletes. However, these studies have focused on the American intercollegiate sport system, which limits the generalizability of results to different contexts. The current study examined the prevalence of suicidality of Canadian student-athletes relative to nonathletes. Varsity athletes ( n = 348) and nonathletes ( n = 9,504) participated in the 2022 Canadian cohort of the American Collegiate Health Association’s National College Health Assessment, which included the revised Suicide Behavior Questionnaire. Student-athletes’ scores on the revised Suicide Behavior Questionnaire were significantly lower than nonathletes, indicating significantly lower suicidality. Stress in the past month was a significant predictor for student-athletes, but not nonathletes. These results are largely consistent with the results from American samples.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.430
Teacher spread0.400 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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